Discrimination of Human Pathogen Clostridium Species Especially of the Heterogeneous C. sporogenes and C. botulinum by MALDI-TOF Mass Spectrometry.

Clostridium species cause several local and systemic diseases. Conventional identification of these microorganisms is in part laborious, not always reliable, time consuming or does not always distinguish different species, i.e., C. botulinum and C. sporogenes. All in, there is a high interest to find out a reliable, powerful and rapid method to identify Clostridium spp. not only on genus but also on species level. The aim of the present study was to identify Clostridium spp. strains and also to find differences and metabolic groups of C. botulinum by Matrix-Assisted Laser Desorption/Ionization Time of Flight Mass Spectrometry (MALDI-TOF MS). A total of 123 strains of Clostridium spp. (C. botulinum, n = 40, C. difficile, n = 11, C. tetani, n = 11, C. sordellii, n = 20, C. sporogenes, n = 18, C. innocuum, n = 10, C. perfringens, n = 13) were analyzed by MALDI-TOF MS in combination with methods of multivariate statistical analysis. MALDI-TOF MS analysis in combination with methods of multivariate statistical analysis was able to discriminate between the different tested Clostridium spp., even between species which are closely related and difficult to differentiate by traditional methods, i.e., C. sporogenes and C. botulinum. Furthermore, the method was able to separate the different metabolic groups of C. botulinum. Especially, E gene-positive C. botulinum strains are clearly distinguishable from the other species but also from those producing other toxin types. Thus, MALDI-TOF MS represents a reliable and above all quick method for identification of cultivated Clostridium species.

Discrimination of Enterobacteriaceae and Non-fermenting Gram Negative Bacilli by MALDI-TOF Mass Spectrometry.

Discrimination of Enterobacteriaceae and Non-fermenting Gram Negative Bacilli by MALDI-TOF Mass Spectrometry Matrix assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) has proven to be an effective identification tool in medical microbiology. Discrimination to subspecies or serovar level has been found to be challenging using commercially available identification software. By forming our own reference database and using alternative analysis methods, we could reliably identify all implemented Enterobacteriaceae and non-fermenting gram negative bacilli by MALDI-TOF MS and even succeeded to distinguish Shigella sonnei from Escherichia coli (E. coli) and Salmonella enterica spp. enterica serovar Enteritidis from Salmonella enterica spp. enterica serovar Typhimurium. Furthermore, the method showed the ability to separate Enterohemorrhagic E. coli (EHEC) and Enteropathogenic E. coli (EPEC) from non-enteropathogenic E. coli.

A step towards the discrimination of beta-lactamase-producing clinical isolates of Enterobacteriaceae and Pseudomonas aeruginosa by MALDI-TOF mass spectrometry.

BACKGROUND: Matrix-Assisted Laser-Desorption/Ionization Time of Flight Mass Spectrometry (MALDI-TOF MS) has already proven to be a powerful tool for species identification in microbiological laboratories. As adequate and rapid screening methods for antibiotic resistance are crucially needed, the present study investigated the discrimination potential of MALDI-TOF MS among extended-spectrum-beta-lactamase (ESBL) or metallo-beta-lactamases- (MBL) producing and the nonproducing strains of Escherichia coli (n=19), Klebsiella pneumoniae (n=19), and Pseudomonas aeruginosa (n=38), respectively. MATERIAL/METHODS: We used a MALDI-TOF MS protocol, usually applied for species identification, in order to integrate a screening method for beta-lactamases into the routine species identification workflow. The acquired spectra were analyzed by visual inspection, statistical similarity analysis and support vector machine (SVM) classification algorithms. RESULTS: Neither visual inspection nor mathematical similarity analysis allowed discrimination between spectra of beta-lactamase-producing and the nonproducing strains, but classification within a species by SVM-based algorithms could achieve a correct classification rate of up to 70%. CONCLUSIONS: This shows that MALDI-TOF MS has definite potential to discriminate antibiotic-resistant strains due to ESBL and MBL production from nonproducing strains, but this performance is not yet sufficiently reliable for routine microbiological diagnostics.